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A Comprehensive Review on Research Methods for Lithium-ion Battery of State of Health Estimation and End of Life Prediction: Methods, Properties, and Prospects

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Enhancing state-of-health estimation for uninterruptible power supply systems using lithium batteries under constant-voltage charging scenario

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A novel state of health estimation model for lithium-ion batteries incorporating signal processing and optimized machine learning methods

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An LLM-Based Framework for State of Health Estimation of Lithium-Ion Batteries

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Improving in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging

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Evaluating Reservoir Spiking Neural Network Configurations for Accurate Battery State-of-Health Prediction

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Implementing High‐Throughput Screening of Organic Solar Cells using Transfer Learning Based on Fine‐Tuning Neural Network Strategy

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A Review of Remaining Useful Life Prediction for Energy Storage Components Based on Stochastic Filtering Methods

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Advanced Functional Optical Fiber Sensors for Smart Battery Monitoring

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Generalizing capacity estimation for cross-domain lithium-ion batteries with deep multi-domain adaptation

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Opportunities and challenges in transformer neural networks for battery state estimation: Charge, health, lifetime, and safety

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Deep learning-based Remaining Useful Life Prediction of Lithium-ion Battery Considering Two-phase Aging Process

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Artificial Intelligence in Electric Vehicle Battery Disassembly: A Systematic Review

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Lithium-ion batteries lifetime early prediction using domain adversarial learning

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Robust battery fault detection for electric mining trucks using deep learning with enhanced interpretabilit

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A deep learning framework for the joint prediction of the SOH and RUL of lithium-ion batteries based on bimodal images

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An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder

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Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis

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A federated transfer learning approach for lithium-ion battery lifespan early prediction considering privacy preservation

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Cross-domain battery SOH and RUL estimation via Domain-Adaptive Transformer

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A multi-scale temporal fusion network for accurate and uncertainty-aware battery remaining useful life prediction

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Support-Sample-Assisted Domain Generalization via Attacks and Defenses: Concepts, Algorithms, and Applications to Pipeline Fault Diagnosis

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A hybrid and efficient architecture for enhanced battery capacity degradation prediction with zero-shot generalization

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A novel feature optimization and ensemble learning method for state-of-health prediction of mining lithium-ion batteries

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Challenges and prospects in real-world battery status prediction within Industry 4.0

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A comprehensive review of remaining useful life prediction methods for lithium-ion batteries: Models, trends, and engineering applications

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Deep Learning-Powered Lifetime Prediction for Lithium-Ion Batteries Based on Small Amounts of Charging Cycles

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A comprehensive review of machine learning-based state of health estimation for lithium-ion batteries: data, features, algorithms, and future challenges

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In-situ battery life prognostics amid mixed operation conditions using physics-driven machine learning

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Health monitoring by optical fiber sensing technology for rechargeable batteries

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A dual-driven interpretable ensemble model for efficient and reliable SOH estimation of lithium-ion batteries

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Revealing the Unique Influential Mechanism of Parallel-Connected Lithium-Ion Cells Based on Current Distribution: The Vectorial Effect among Cell-to-Cell Parameters

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Split Multi-Task Federated Learning for Battery Health and Capacity Estimation in Electric Vehicles

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Comprehensive testing technology for new energy vehicle power batteries based on improved particle swarm optimization

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Ultra-early prediction of lithium-ion battery performance using mechanism and data-driven fusion model

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Joint prediction of SOH and RUL for Lithium-ion batteries by an enhanced Transformer model with physical information constraints

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Fault decoupling in hydraulic systems: A large language model-assisted dual-stream multi-task learning approach

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End-to-end millisecond-level battery aging diagnostics for electric vehicles

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Unlocking the potential of unlabeled data: Self-supervised machine learning for battery aging diagnosis with real-world field data

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A Novel Method for State of Health Estimation of Lithium-Ion Batteries Based on Deep Learning Neural Network and Transfer Learning

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Neural Representation-Based Wiener Process With Meta-Learning for Battery RUL Prediction Under Time-Varying Degradation Rate

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A deep learning approach incorporating attention mechanism and transfer learning for lithium-ion battery lifespan prediction

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Battery health diagnostics: Bridging the gap between academia and industry

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Lithium-ion battery state-of-health estimation using intra-domain and cross-domain transfer learning: mitigating domain shift based on Wasserstein distance

Chenglong Duan, Hung Le and Dazhong Wu

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Unlocking Interpretable Prediction of Battery Random Discharge Capacity With Domain Adaptative Physics Constraint

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Historical data-independent remaining useful life prediction method based on dual-input deep learning neural network

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Simultaneous Estimation of State of Health and Remaining Useful Life for Lithium-ion Batteries Using a Transfer-Learning-Based Fusion Model

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Inconsistency identification for Lithium-ion battery energy storage systems using deep embedded clustering

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Battery safety: Machine learning-based prognostics

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Stress-informed transfer learning: Accelerated battery life evaluation model across diverse operating conditions and cell mechanisms

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Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach

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Physics-informed transfer learning by embedding physics into activation functions: an application in battery health management

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A transferable long-term lithium-ion battery aging trajectory prediction model considering internal resistance and capacity regeneration phenomenon

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Predicting the Future Capacity and Remaining Useful Life of Lithium-Ion Batteries Based on Deep Transfer Learning

Chenyu Sun, Taolin Lu, Qingbo Li, Yili Liu, Wen Yang and Jingying Xie

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Masked Self-Supervised Transformer Framework for State-of-Health Estimation of Electric Vehicle Lithium Batteries

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Recent deep learning models for diagnosis and health monitoring: A review of research works and future challenges

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Bidirectional-Mamba-based iterative prediction for long-cycle battery remaining useful life with physical constraints

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A CNN‐LSTM Method Based on Voltage Deviation for Predicting the State of Health of Lithium‐Ion Batteries

Fen Xiao, Wei Yang, Yanhuai Ding, Xiang Li, Kehang Zhang and Jiaxiong Liu

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Recent progress in state of health estimation for lithium-ion batteries: From laboratory to practical application

Shiyi Fu, Hongtao Fan, Zhaorui Jin, Fan Ji, Yulin Tao, Yachao Dong, Xunyuan Chen, Minghao Shao, Shuyu Yuan, Yu Wang and Yaojie Sun

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Battery health prognosis in data-deficient practical scenarios via reconstructed voltage-based machine learning

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State of Health Estimation of Lithium‐ion Batteries Based on Machine Learning with Mechanical‐Electrical Features

Lili Gong, Zhiyuan Zhang, Xueyan Li, Kai Sun, Haosong Yang, Bin Li, Hong Ye, Xiaoyang Wang and Peng Tan

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A multi-time-resolution attention-based interaction network for co-estimation of multiple battery states

Ruixue Liu and Benben Jiang

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Transfer-driven prognosis from battery cells to packs: An application with adaptive differential model decomposition

Dongzhen Lyu, Enhui Liu, Huiling Chen, Bin Zhang and Jiawei Xiang

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Early Prediction of Knee Point and Knee Capacity for Fast-Charging Lithium-Ion Battery With Uncertainty Quantification and Calibration

Yuqi Ke, Yiyue Jiang, Rong Zhu, Weiwen Peng and Xiaojun Tan

IEEE Trans. Transp. Electrific., 2024, 10, 2873
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Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks

Sungho Suh, Dhruv Aditya Mittal, Hymalai Bello, Bo Zhou, Mayank Shekhar Jha and Paul Lukowicz

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A meta fusion model combining geographic data and twitter sentiment analysis for predicting accident severity

Areeba Naseem Khan, Yaser Ali Shah, Wasiat Khan, Amaad Khalil and Jebran Khan

Sci Rep, 2025, 15
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Battery prognostics and health management from a machine learning perspective

Jingyuan Zhao, Xuning Feng, Quanquan Pang, Junbin Wang, Yubo Lian, Minggao Ouyang and Andrew F. Burke

Journal of Power Sources, 2023, 581, 233474
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Data‐Driven Online Prognosis of Rechargeable Batteries: Prospect and Perspective

Kun‐Yu Liu, Ting‐Ting Wang, Xinyan Liu and Hong‐Jie Peng

Batteries & Supercaps, 2024, 7
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Detection of the knee point in lithium-ion battery degradation using a state-of-charge-dependent parameter

Hyunjae Kim, Inwoo Kim, Minsoo Kim, Seongha An, Hyo Chul Ahn, Dongmin Park, Jun Hee Lee, Chun Yong Kang and Jang Wook Choi

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Exploring life warning solution of lithium-ion batteries in real-world scenarios: TCN-transformer fusion model for battery pack SOH estimation

Yuan Chen, Dongyuan Li, Xiaohe Huang, Jichao Hong, Chaoxu Mu, Longxing Wu and Kerui Li

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Data-driven estimation of battery state-of-health with formation features

Weilin He, Dingquan Li, Zhongxian Sun, Chenyang Wang, Shihai Tang, Jing Chen, Xin Geng, Hailong Wang, Zhimeng Liu, Linyu Hu, Dongchen Yang, Haiyan Tu, Yuanjing Lin and Xin He

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Early-stage degradation trajectory prediction for lithium-ion batteries: A generalized method across diverse operational conditions

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Journal of Power Sources, 2024, 612, 234808
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Battery cumulative lifetime prognostics to bridge laboratory and real-life scenarios

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Automatic Fault Classification in Photovoltaic Modules Using Denoising Diffusion Probabilistic Model, Generative Adversarial Networks, and Convolutional Neural Networks

Carlos Roberto da Silveira Junior, Carlos Eduardo Rocha Sousa and Ricardo Henrique Fonseca Alves

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Intelligent battery life management through mechanism and machine learning under real vehicle working conditions

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Integration of topological data analysis and entropy features for the prediction of lithium-ion battery state-of-health

Manoj K. Singh, Anuj Kumar, Sangeeta Pant, Shshank Chaube, Kriti Misra, Jitendra Pal Singh and Ketan Kotecha

Future Batteries, 2025, 6, 100059
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